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Proceedings Paper

Recognition of two-person interaction in multi-view surveillance video via proxemics cues and spatio-temporal interest points
Author(s): Bo Zhang; Paolo Rota; Nicola Conci
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Paper Abstract

In this paper we propose a novel method to recognize different types of two-person interactions through multi-view surveillance cameras. From the bird-eye view, proxemics cues are exploited to segment the duration of the interaction, while from the lateral view the corresponding interaction intervals are extracted. The classification is achieved by applying a visual bag-of-words approach, which is used to train a liner multi-class SVM classifier. We test our method on the UNITN social interaction dataset. Experimental results show that using the temporal segmentation can improve the classification performance.

Paper Details

Date Published: 19 March 2013
PDF: 7 pages
Proc. SPIE 8663, Video Surveillance and Transportation Imaging Applications, 866305 (19 March 2013); doi: 10.1117/12.2003686
Show Author Affiliations
Bo Zhang, Univ. degli Studi di Trento (Italy)
Paolo Rota, Univ. degli Studi di Trento (Italy)
Nicola Conci, Univ. degli Studi di Trento (Italy)


Published in SPIE Proceedings Vol. 8663:
Video Surveillance and Transportation Imaging Applications
Robert Paul Loce; Eli Saber, Editor(s)

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